Search results for: human auditory system model

Authors: Mengke Zhan, Cheng-Gang Xie, Jian-Jun Shu

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A venturi flowmeter is a common device used in multiphase flow rate measurement in the upstream oil and gas industry. Having a robust computational model for multiphase flow in a venturi is desirable for understanding the gas-liquid and fluid-pipe interactions and predicting pressure and phase distributions under various flow conditions. A steady Eulerian-Eulerian framework is used to simulate upward gas-liquid flow in a vertical venturi. The simulation results are compared with experimental measurements of venturi differential pressure and chord-averaged gas holdup in the venturi throat section. The choice of turbulence model is nontrivial in the multiphase flow modelling in a venturi. The performance cross-comparison of the k-ϵ model, Reynolds stress model (RSM) and shear-stress transport (SST) k-ω turbulence model is made in the study. In terms of accuracy and computational cost, the SST k-ω turbulence model is observed to be the most efficient.

Keywords: computational fluid dynamics (CFD), gas-liquid flow, turbulence modelling, venturi

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Authors: Maulana Ayoub Ali, Pradeep Kulshrestha

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Laws of any given secular state have a huge contribution in the growth of the Islamic banking system because the system uses conventional laws to govern its activities. Therefore, the former should be ready to accommodate the latter in order to make the Islamic banking system work properly without affecting the current conventional banking system and therefore without affecting its system. Islamic financial rules have been practiced since the birth of Islam. Following the recent world economic challenges in the financial sector, a quick rebirth of the contemporary Islamic ethical banking system took place. The coming of the Islamic banking system is due to various reasons including but not limited to the failure of the interest based economy in solving financial problems around the globe. Therefore, the Islamic banking system has been adopted as an alternative banking system in order to recover the highly damaged global financial sector. But the Islamic banking system has been facing a number of challenges which hinder its smooth operation in different parts of the world. It has not been the aim of this paper to discuss other challenges rather than the legal ones, but the same was partly discussed when it was justified that it was proper to do so. Generally, there are so many things which have been discovered in the course of writing this paper. The most important part is the issue of the regulatory and supervisory framework for the Islamic banking system in Tanzania and in other nations is considered to be a crucial part for the development of the Islamic banking industry. This paper analyses what has been observed in the study on that area and recommends for necessary actions to be taken on board in a bid to make Islamic banking system reach its climax of serving the larger community by providing ethical, equitable, affordable, interest-free and society cantered banking system around the globe.

Keywords: Islamic banking, interest free banking, ethical banking, legal framework

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Authors: Snehal D. Ganjave, Hardik Dodia, Avinash V. Sunder, Swati Madhu, Pramod P. Wangikar

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Batch cultivation of recombinant bacteria in shake flasks results in low cell density due to nutrient depletion. Previous protocols on high cell density cultivation in shake flasks have relied mainly on controlled release mechanisms and extended cultivation protocols. In the present work, we report an optimized fed-batch process for high cell density cultivation of recombinant E. coli BL21(DE3) for protein production. A cybernetic model-based, multi-objective optimization strategy was implemented to obtain the optimum operating variables to achieve maximum biomass and minimized substrate feed rate. A syringe pump was used to feed a mixture of glycerol and yeast extract into the shake flask. Preliminary experiments were conducted with online monitoring of dissolved oxygen (DO) and offline measurements of biomass and glycerol to estimate the model parameters. Multi-objective optimization was performed to obtain the pareto front surface. The selected optimized recipe was tested for a range of proteins that show different extent soluble expression in E. coli. These included eYFP and LkADH, which are largely expressed in soluble fractions, CbFDH and GcanADH , which are partially soluble, and human PDGF, which forms inclusion bodies. The biomass concentrations achieved in 24 h were in the range 19.9-21.5 g/L, while the model predicted value was 19.44 g/L. The process was successfully reproduced in a standard laboratory shake flask without online monitoring of DO and pH. The optimized fed-batch process showed significant improvement in both the biomass and protein production of the tested recombinant proteins compared to batch cultivation. The proposed process will have significant implications in the routine cultivation of E. coli for various applications.

Keywords: cybernetic model, E. coli, high cell density cultivation, multi-objective optimization

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Authors: Mamta Rajbhar, Sanjay K. Mohanty

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India's progress in achieving replacement level of fertility is largely contingent on fertility reduction in the state of Uttar Pradesh as it accounts 17% of India's population with a low level of development. Though the TFR in the state has declined from 5.1 in 1991 to 3.4 by 2011, it conceals large differences in fertility level across districts. Using data from multiple sources this paper tests the hypothesis that the improvement in human development significantly reduces the fertility levels in districts of Uttar Pradesh. The unit of analyses is district, and fertility estimates are derived using the reverse survival method(RSM) while human development indices(HDI) are are estimated using uniform methodology adopted by UNDP for three period. The correlation and linear regression models are used to examine the relationship of fertility change and human development indices across districts. Result show the large variation and significant change in fertility level among the districts of Uttar Pradesh. During 1991-2011, eight districts had experienced a decline of TFR by 10-20%, 30 districts by 20-30% and 32 districts had experienced decline of more than 30%. On human development aspect, 17 districts recorded increase of more than 0.170 in HDI, 18 districts in the range of 0.150-0.170, 29 districts between 0.125-0.150 and six districts in the range of 0.1-0.125 during 1991-2011. Study shows significant negative relationship between HDI and TFR. HDI alone explains 70% variation in TFR. Also, the regression coefficient of TFR and HDI has become stronger over time; from -0.524 in 1991, -0.7477 by 2001 and -0.7181 by 2010. The regression analyses indicate that 0.1 point increase in HDI value will lead to 0.78 point decline in TFR. The HDI alone explains 70% variation in TFR. Improving the HDI will certainly reduce the fertility level in the districts.

Keywords: Fertility, HDI, Uttar Pradesh

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Authors: Jelena R. Pejović, Nina N. Serdar

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This paper presents an analysis of the “Performance-Based” seismic design method, in order to overcome the perceived disadvantages and limitations of the existing seismic design approach based on force, in engineering practice. Bearing in mind, the specificity of the earthquake as a load and the fact that the seismic resistance of the structures solely depends on its behaviour in the nonlinear field, traditional seismic design approach based on force and linear analysis is not adequate. “Performance-Based” seismic design method is based on nonlinear analysis and can be used in everyday engineering practice. This paper presents the application of this method to eight-story high reinforced concrete building with combined structural system (reinforced concrete frame structural system in one direction and reinforced concrete ductile wall system in other direction). The nonlinear time-history analysis is performed on the spatial model of the structure using program Perform 3D, where the structure is exposed to forty real earthquake records. For considered building, large number of results were obtained. It was concluded that using this method we could, with a high degree of reliability, evaluate structural behavior under earthquake. It is obtained significant differences in the response of structures to various earthquake records. Also analysis showed that frame structural system had not performed well at the effect of earthquake records on soil like sand and gravel, while a ductile wall system had a satisfactory behavior on different types of soils.

Keywords: ductile wall, frame system, nonlinear time-history analysis, performance-based methodology, RC building

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Authors: Kyeong Hoon Park, Taiji Mazuda

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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.

Keywords: base-isolation, bilinear model, high damping rubber, loading test

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Authors: Iván González, Pablo Andrés Maya, Sebastián Jaén

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Eco-industrial parks (EIPs) work as networks for the exchange of by-products, such as materials, water, or energy. This research identifies the relevant factors in the formation of EIPs in different industrial environments around the world. Then an aggregation of these factors is carried out to reduce them from 50 to 17 and classify them according to 5 fundamental axes. Subsequently, the Vester Sensitivity Model (VSM) systemic methodology is used to determine the influence of the 17 factors on an EIP system and the interrelationship between them. The results show that the sequence of effects between factors: Trust and Cooperation → Business Association → Flows → Additional Income represents the “backbone” of the system, being the most significant chain of influences. In addition, the Organizational Culture represents the turning point of the Industrial Symbiosis on which it must act correctly to avoid falling into unsustainable economic development. Finally, the flow of Information should not be lost since it is what feeds trust between the parties, and the latter strengthens the system in the face of individual or global imbalances. This systemic understanding will enable the formulation of pertinent policies by the actors that interact in the formation and permanence of the EIP. In this way, it seeks to promote large-scale sustainable industrial development, integrating various community actors, which in turn will give greater awareness and appropriation of the current importance of sustainability in industrial production.

Keywords: critical factors, eco-industrial park, industrial symbiosis, system methodology

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: forecasting model, steel demand uncertainty, hierarchical Bayesian framework, exponential smoothing method

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Authors: Enya Trenholm-Jensen

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This paper employs various semiotic methodologies to examine the mechanism of soft power. Soft power refers to a country’s global reputation and their ability to leverage that reputation to achieve certain aims. South Korea has invested heavily in their soft power strategy for a multitude of predominantly historical and geopolitical reasons. On account of this investment and the global prominence of their strategy, South Korea was considered to be the optimal candidate for the aims of this investigation. Having isolated the entertainment industry as one of the most heavily funded segments of the South Korean soft power strategy, the analysis restricted itself to this sector. Within this industry, two entertainment products were selected as case studies. The case studies were chosen based on commercial success according to metrics such as streams, purchases, and subsequent revenue. This criterion was deemed to be the most objective and verifiable indicator of the products general appeal. The entertainment products which met the chosen criterion were Netflix’ “Squid Game” and BTS’ hit single “Butter”. The methodologies employed were chosen according to the medium of the entertainment products. For “Squid Game,” an aesthetic analysis was carried out to investigate how multi- layered meanings were mobilized in a show popularized by its visual grammar. To examine “Butter”, both music semiology and linguistic analysis were employed. The music section featured an analysis underpinned by denotative and connotative music semiotic theories borrowing from scholars Theo van Leeuwen and Martin Irvine. The linguistic analysis focused on stance and semantic fields according to scholarship by George Yule and John W. DuBois. The aesthetic analysis of the first case study revealed intertextual references to famous artworks, which served to augment the emotional provocation of the Squid Game narrative. For the second case study, the findings exposed a set of musical meaning units arranged in a patchwork of familiar and futuristic elements to achieve a song that existed on the boundary between old and new. The linguistic analysis of the song’s lyrics found a deceptively innocuous surface level meaning that bore implications for authority, intimacy, and commercial success. Whether through means of visual metaphor, embedded auditory associations, or linguistic subtext, the collective findings of the three analyses exhibited a desire to conjure a form of positive arousal in the spectator. In the synthesis section, this process is likened to that of branding. Through an exploration of branding, the entertainment products can be understood as cogs in a larger operation aiming to create positive associations to Korea as a country and a concept. Limitations in the form of a timeframe biased perspective are addressed, and directions for future research are suggested. This paper employs semiotic methodologies to examine two entertainment products as mechanisms of soft power. Through means of visual metaphor, embedded auditory associations, or linguistic subtext, the findings reveal a desire to conjure positive arousal in the spectator. The synthesis finds similarities to branding, thus positioning the entertainment products as cogs in a larger operation aiming to create positive associations to Korea as a country and a concept.

Keywords: BTS, cognitive semiotics, entertainment, soft power, south korea, squid game

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Authors: Tabrej Khan

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Examination Scheduling System (ESS) is a scheduling system that targets as an exam committee in any academic institute to help them in managing the exams automatically. We present an algorithm for Examination Scheduling System. Nowadays, many universities have challenges with creating examination schedule fast with less confliction compared to hand works. Our aims are to develop a computerized system that can be used in examination scheduling in an academic institute versus available resources (Time, Hall, Invigilator and instructor) with no contradiction and achieve fairness among students. ESS was developed using HTML, C# language, Crystal Report and ASP.NET through Microsoft Visual Studio 2010 as developing tools with integrated SQL server database. This application can produce some benefits such as reducing the time spent in creating an exam schedule and achieving fairness among students

Keywords: examination scheduling system (ESS), algorithm, ASP.NET, crystal report

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Authors: Cemil Kutluturk

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This is a comparative study of the incarnation of God according to Hinduism and Christianity. After dealing with their basic ideas on the concept of the incarnation of God, the main similarities and differences between each other will be examined by quoting references from their sacred texts. In Hinduism, the term avatara is used in order to indicate the concept of the incarnation of God. The word avatara is derived from ava (down) and tri (to cross, to save, attain). Thus avatara means to come down or to descend. Although an avatara is commonly considered as an appearance of any deity on earth, the term refers particularly to descents of Vishnu. According to Hinduism, God becomes an avatara in every age and entering into diverse wombs for the sake of establishing righteousness. On the Christian side, the word incarnation means enfleshment. In Christianity, it is believed that the Logos or Word, the Second Person of Trinity, presumed human reality. Incarnation refers both to the act of God becoming a human being and to the result of his action, namely the permanent union of the divine and human natures in the one Person of the Word. When the doctrines of incarnation and avatara are compared some similarities and differences can be found between each other. The basic similarity is that both doctrines are not bound by the laws of nature as human beings are. They reveal God’s personal love and concern, and emphasize loving devotion. Their entry into the world is generally accompanied by extraordinary signs. In both cases, the descent of God allows for human beings to ascend to God. On the other hand, there are some distinctions between two religious traditions. For instance, according to Hinduism there are many and repeated avataras, while Christ comes only once. Indeed, this is related to the respective cyclic and linear worldviews of the two religions. Another difference is that in Hinduism avataras are real and perfect, while in Christianity Christ is also real, yet imperfect; that is, he has human imperfections, except sin. While Christ has never been thought of as a partial incarnation, in Hinduism there are some partial and full avataras. The other difference is that while the purpose of Christ is primarily ultimate salvation, not every avatara grants ultimate liberation, some of them come only to save a devotee from a specific predicament.

Keywords: Avatara, Christianity, Hinduism, incarnation

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Authors: C. J. Coetzee, E. Horn

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One of the main challenges in using the Discrete Element Method (DEM) is to specify the correct input parameter values. In general, the models are sensitive to the input parameter values and accurate results can only be achieved if the correct values are specified. For the linear contact model, micro-parameters such as the particle density, stiffness, coefficient of friction, as well as the particle size and shape distributions are required. There is a need for a procedure to accurately calibrate these parameters before any attempt can be made to accurately model a complete bulk materials handling system. Since DEM is often used to model applications in the mining and quarrying industries, a calibration procedure was developed for materials that consist of relatively large (up to 40 mm in size) particles. A coarse crushed aggregate was used as the test material. Using a specially designed large shear box with a diameter of 590 mm, the confined Young’s modulus (bulk stiffness) and internal friction angle of the material were measured by means of the confined compression test and the direct shear test respectively. DEM models of the experimental setup were developed and the input parameter values were varied iteratively until a close correlation between the experimental and numerical results was achieved. The calibration process was validated by modelling the pull-out of an anchor from a bed of material. The model results compared well with experimental measurement.

Keywords: Discrete Element Method (DEM), calibration, shear box, anchor pull-out

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Authors: Kristina Sutiene, Lina Dapkute

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The paper investigates the current demographic trends that exert the sustainability of pension systems in most EU regions. Several drivers usually compose the demographic challenge, coming from the structure and trends of population in the country. As the case of research, three main variables of demographic risk in Lithuania have been singled out and have been used in making up the analysis. Over the last two decades, the country has presented a peculiar demographic situation characterized by pessimistic fertility trends, negative net migration rate and rising life expectancy that make the significant changes in labor-age population. This study, therefore, sets out to assess the relative impact of these risk factors both individually and in aggregate, while assuming economic trends to evolve historically. The evidence is presented using data of pension funds that operate in Lithuania and are financed by defined-contribution plans. To achieve this goal, the discrete-time pension fund’s value model is developed that reflects main operational modalities: contribution income from current participants and new entrants, pension disbursement and administrative expenses; it also fluctuates based on returns from investment activity. Age-structured Leslie population dynamics model has been integrated into the main model to describe the dynamics of fertility, migration and mortality rates upon age. Validation has concluded that Leslie model adequately fits the current population trends in Lithuania. The elasticity of pension system is examined using Loimaranta efficiency as a measure for comparison of plausible long-term developments of demographic risks. With respect to the research question, it was found that demographic risks have different levels of influence on future value of aggregated pension funds: The fertility rates have the highest importance, while mortality rates give only a minor impact. Further studies regarding the role of trying out different economic scenarios in the integrated model would be worthwhile.

Keywords: asset liability modelling, Leslie model, pension funds, population dynamics

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Authors: Benjamin Beltzung, Marie Pelé, Julien P. Renoult, Cédric Sueur

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To this day, it is not known if drawing is specifically human behavior or if this behavior finds its origins in ancestor species. An interesting window to enlighten this question is to analyze the drawing behavior in genetically close to human species, such as non-human primate species. A good candidate for this approach is the orangutan, who shares 97% of our genes and exhibits multiple human-like behaviors. Focusing on figurative aspects may not be suitable for orangutans’ drawings, which may appear as scribbles but may have meaning. A manual feature selection would lead to an anthropocentric bias, as the features selected by humans may not match with those relevant for orangutans. In the present study, we used deep learning to analyze the drawings of a female orangutan named Molly († in 2011), who has produced 1,299 drawings in her last five years as part of a behavioral enrichment program at the Tama Zoo in Japan. We investigate multiple ways to decipher Molly’s drawings. First, we demonstrate the existence of differences between seasons by training a deep learning model to classify Molly’s drawings according to the seasons. Then, to understand and interpret these seasonal differences, we analyze how the information spreads within the network, from shallow to deep layers, where early layers encode simple local features and deep layers encode more complex and global information. More precisely, we investigate the impact of feature complexity on classification accuracy through features extraction fed to a Support Vector Machine. Last, we leverage style transfer to dissociate features associated with drawing style from those describing the representational content and analyze the relative importance of these two types of features in explaining seasonal variation. Content features were relevant for the classification, showing the presence of meaning in these non-figurative drawings and the ability of deep learning to decipher these differences. The style of the drawings was also relevant, as style features encoded enough information to have a classification better than random. The accuracy of style features was higher for deeper layers, demonstrating and highlighting the variation of style between seasons in Molly’s drawings. Through this study, we demonstrate how deep learning can help at finding meanings in non-figurative drawings and interpret these differences.

Keywords: cognition, deep learning, drawing behavior, interpretability

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Authors: Bindu Shrestha, Sudarshan R. Tiwari, Sushil B. Bajracharya

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Urban household cooking fuel choice is highly influenced by human behavior and energy culture parameters such as cognitive norms, material culture and practices. Although these parameters have a leading role in Kathmandu for cleaner households, they are not incorporated in the city’s energy policy. This paper aims to identify trade-offs to transform resident behavior in cooking pattern towards cleaner technology from the questionnaire survey, observation, mapping, interview, and quantitative analysis. The analysis recommends implementing a Collaborative Cultural Model (CCM) for changing impact on the neighborhood from the policy level. The results showed that each household produces 439.56 kg of carbon emission each year and 20 percent used unclean technology due to low-income level. Residents who used liquefied petroleum gas (LPG) as their cooking fuel suffered from an energy crisis every year that has created fuel hoarding, which ultimately creates more energy demand and carbon exposure. In conclusion, the carbon emission can be reduced by improving the residents’ energy consumption culture. It recommended the city to use holistic action of changing habits as soft power of collaboration in two-way participation approach within residents, private sectors, and government to change their energy culture and behavior in policy level.

Keywords: energy consumption pattern, collaborative cultural model, energy culture, fuel stacking

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Authors: Vladimir Ryabov, Mikhail Baryshevs, Mikhail Voskresenskey, Boris Popov

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The human prostate gland (PG) samples were obtained from patients who had undergone radical prostatectomy for prostate cancer (PC) and used to extract total RNA and prepare the prostate stromal cell cultures (PSCC) and patients-derived organoids (PDO). Growth of the cell cultures was accessed under microscopic evaluation in transmitted light and the marker expression by reverse polymerase chain reaction (RT-PCR), immunofluorescence, and immunoblotting. Some PCR products from prostate tissue, PSCC, and PDO were cloned and sequenced. We found that the cells of early and late passages of PSCC and corresponding PDO expressed luminal (androgen receptor, AR; cytokeratin 18, CK18) and basal (CK5, p63) epithelial markers, the production of which decreased or disappeared in late PSCC and PDO. The PSCC and PDO of early passages from cancer tissue additionally produced cancer markers AMACR, TMPRSS2-ERG, and Ezh2. The expression of TMPRSS2-ERG fusion transcripts was verified by cloning and sequencing the PCR products. The results obtained suggest that early passages of PSCC might be used as a pre-clinical model for the evaluation of early markers of prostate cancer.

Keywords: localized prostate cancer, prostate epithelial markers, prostate cancer markers, AMACR, TMPRSS2-ERG, prostate stromal cell cultures, PDO

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Authors: Hung Lin-Zin, Lai Mei-Yen

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Prostate cancer is the most commonly diagnosed male cancer in the U.S. The prevalence is around 1 in 8. The etiology of prostate cancer is still unknown, but some predisposing factors, such as age, black race, family history, and obesity, may increase the risk of the disease. In 2020, a total of 7,178 Taiwanese people were nearly diagnosed with prostate cancer, accounting for 5.88% of all cancer cases, and the incidence rate ranked fifth among men. In that year, the total number of deaths from prostate cancer was 1,730, accounting for 3.45% of all cancer deaths, and the death rate ranked 6th among men, accounting for 94.34% of the cases of male reproductive organs. Looking for domestic and foreign literature on the use of OMOP (Observational Medical Outcomes Partnership, hereinafter referred to as OMOP) database analysis, there are currently nearly a hundred literature published related to nursing-related health problems and nursing measures built in the OMOP general data model database of medical institutions are extremely rare. The OMOP common data model construction analysis platform is a system developed by the FDA in 2007, using a common data model (common data model, CDM) to analyze and monitor healthcare data. It is important to build up relevant nursing information from the OMOP- CDM database to assist our daily practice. Therefore, we choose prostate cancer patients who are our popular care objects and use the OMOP- CDM database to explore the common associated health problems. With the assistance of OMOP-CDM database analysis, we can expect early diagnosis and prevention of prostate cancer patients' comorbidities to improve patient care.

Keywords: OMOP, nursing diagnosis, health problem, prostate cancer

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Authors: Tanapon Keatsamarn, Chuchart Pintavirooj

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Foot pressure measurement provides necessary information for diagnosis diseases, foot insole design, disorder prevention and other application. In this paper, dynamic foot pressure measurement is presented for pressure measuring with high resolution and accuracy. The dynamic foot pressure measurement system consists of hardware and software system. The hardware system uses a transparent acrylic plate and uses steel as the base. The glossy white paper is placed on the top of the transparent acrylic plate and covering with a black acrylic on the system to block external light. Lighting from LED strip entering around the transparent acrylic plate. The optical sensors, the digital cameras, are underneath the acrylic plate facing upwards. They have connected with software system to process and record foot pressure video in avi file. Visual Studio 2017 is used for software system using OpenCV library.

Keywords: foot, foot pressure, image processing, optical sensors

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Authors: Ahmed M. Ashteyat

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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.

Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling

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Authors: Ibrahim Laro ABUBAKAR

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The study examined the Availability and Utilization of E-Learning Technologies in Teaching of Human Kinetics and Health Education courses in Nigerian Universities, specifically, Universities in Kwara State. Two purposes were formulated to guide the study from which two research questions and two hypotheses were raised. The descriptive research design was used in the research. Three Hundred respondents (100 Lecturers and 200 Students) made up the population for the study. There was no sampling, as the population of the study was not much. A structured questionnaire tagged ‘Availability and Utilization of E-Learning Technologies in Teaching and Learning Questionnaire’ (AUETTLQ) was used for data collection. The questionnaire was subjected to face and content validation, and it was equally pilot tested. The validation yielded a reliability coefficient of 0.78. The data collected from the study were statistically analyzed using frequencies and percentage count for personal data of the respondents, mean and standard deviation to answer the research questions. The null hypotheses were tested at 0.05 level of significance using the independent t-test. One among other findings of this study showed that lecturers and Student are aware of synchronous e-learning technologies in teaching and learning of Human Kinetics and Health Education but often utilize the synchronous e-learning technologies. It was recommended among others that lecturers and Students should be sensitized through seminars and workshops on the need to maximally utilize available e-learning technologies in teaching and learning of Human Kinetics and Health Education courses in Universities.

Keywords: awareness, utilization, E-Learning, technologies, human kinetics synchronous

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Authors: Surbhi Mathur, J. M. Vyas

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Although the rapid development of forensic speaker recognition technology has been conducted, there are still many problems to be solved. The biggest problem arises when the cases involving disguised voice samples come across for the purpose of examination and identification. Such type of voice samples of anonymous callers is frequently encountered in crimes involving kidnapping, blackmailing, hoax extortion and many more, where the speaker makes a deliberate effort to manipulate their natural voice in order to conceal their identity due to the fear of being caught. Voice disguise causes serious damage to the natural vocal parameters of the speakers and thus complicates the process of identification. The sole objective of this doctoral project is to find out the possibility of rendering definite opinions in cases involving disguised speech by experimentally determining the effects of different disguise forms on personal identification and percentage rate of speaker recognition for various voice disguise techniques such as raised pitch, lower pitch, increased nasality, covering the mouth, constricting tract, obstacle in mouth etc by analyzing and comparing the amount of phonetic and acoustic variation in of artificial (disguised) and natural sample of an individual, by auditory as well as spectrographic analysis.

Keywords: forensic, speaker recognition, voice, speech, disguise, identification

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Authors: Mohammed T. Hayajneh

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Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

Procedia PDF Downloads 382

Authors: Ma Yuzhe, Burra Venkata Durga Kumar

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The computer is a great invention. As people use computers more and more frequently, the demand for PCs is growing, and the performance of computer hardware is also rising to face more complex processing and operation. However, the operating system, which provides the soul for computers, has stopped developing at a stage. In the face of the high price of UNIX (Uniplexed Information and Computering System), batch after batch of personal computer owners can only give up. Disk Operating System is too simple and difficult to bring innovation into play, which is not a good choice. And MacOS is a special operating system for Apple computers, and it can not be widely used on personal computers. In this environment, Linux, based on the UNIX system, was born. Linux combines the advantages of the operating system and is composed of many microkernels, which is relatively powerful in the core architecture. Linux system supports all Internet protocols, so it has very good network functions. Linux supports multiple users. Each user has no influence on their own files. Linux can also multitask and run different programs independently at the same time. Linux is a completely open source operating system. Users can obtain and modify the source code for free. Because of these advantages of Linux, it has also attracted a large number of users and programmers. The Linux system is also constantly upgraded and improved. It has also issued many different versions, which are suitable for community use and commercial use. Linux system has good security because it relies on a file partition system. However, due to the constant updating of vulnerabilities and hazards, the using security of the operating system also needs to be paid more attention to. This article will focus on the analysis and discussion of Linux security issues.

Keywords: Linux, operating system, system management, security

Procedia PDF Downloads 103

Authors: Anil Kumar

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Public Bicycle System (PBS), generally known as Public Bicycle Share System or Bike-Share, is a service provided to the everyday commuters in which several cycles are available on the shared system. The concept of PBS is new to the people of India and requires more study in the fields of essential requirements, major infrastructural requirements, social acceptability, and various challenges. In various Indian cities, MRTS, BRTS, Monorail, and other modes of transport have been adopted for the main haul of transport. These modes take more time, space and are also expensive to implement. At the same time, the PBS system is more economical and takes less time to implement. The main benefit of the PBS system is that it is more environmentally friendly. PBS is being implemented in many Indian cities for public use, but various challenges are associated with this. The study aims to determine what are the basic infrastructural requirements for PBS in India, as well as to determine to what extent a Public Bike Sharing System can provide a quality and efficient service to passengers as a primary method of transportation.

Keywords: public bicycle sharing system, sustainable transport, infrastructure, smart city

Procedia PDF Downloads 187

Authors: Muhammad Qasim, Dolors Puigjaner, Josep Maria López, Joan Herrero, Carme Olivé, Gerard Fortuny

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Computational modeling of the human pelvis using the finite element (FE) method has become extremely important to understand the mechanics of prostate motion and deformation when transrectal ultrasound (TRUS) guided biopsy is performed. The number of reliable and validated hyperelastic constitutive FE models of the male pelvis region is limited, and given models did not precisely describe the anatomical behavior of pelvis organs, mainly of the prostate and its neoplasms location. The motion and deformation of the prostate during TRUS-guided biopsy makes it difficult to know the location of potential lesions in advance. When using this procedure, practitioners can only provide roughly estimations for the lesions locations. Consequently, multiple biopsy samples are required to target one single lesion. In this study, the whole pelvis model (comprised of the rectum, bladder, pelvic muscles, prostate transitional zone (TZ), and peripheral zone (PZ)) is used for the simulation results. An isotropic hyperelastic approach (Signorini model) was used for all the soft tissues except the vesical muscles. The vesical muscles are assumed to have a linear elastic behavior due to the lack of experimental data to determine the constants involved in hyperelastic models. The tissues and organ geometry is taken from the existing literature for 3D meshes. Then the biomechanical parameters were obtained under different testing techniques described in the literature. The acquired parametric values for uniaxial stress/strain data are used in the Signorini model to see the anatomical behavior of the pelvis model. The five mesh nodes in terms of small prostate lesions are selected prior to biopsy and each lesion’s final position is targeted when TRUS probe force of 30 N is applied at the inside rectum wall. Code_Aster open-source software is used for numerical simulations. Moreover, the overall effects of pelvis organ deformation were demonstrated when TRUS–guided biopsy is induced. The deformation of the prostate and neoplasms displacement showed that the appropriate material properties to organs altered the resulting lesion's migration parametrically. As a result, the distance traveled by these lesions ranged between 3.77 and 9.42 mm. The lesion displacement and organ deformation are compared and analyzed with our previous study in which we used linear elastic properties for all pelvic organs. Furthermore, the visual comparison of axial and sagittal slices are also compared, which is taken for Magnetic Resource Imaging (MRI) and TRUS images with our preliminary study.

Keywords: code-aster, magnetic resonance imaging, neoplasms, transrectal ultrasound, TRUS-guided biopsy

Procedia PDF Downloads 84

Authors: Budihardjo Sarwo Sastrosudiro, Arnas Lubis, Muhammad Idrus Alhamid, Nasruddin Jusuf

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Solar thermal cooling system was installed on Mechanical Research Center (MRC) Building that is located in Universitas Indonesia, Depok, Indonesia. It is the first cooling system in Indonesia that utilizes solar energy as energy input combined with natural gas; therefore, the control system must be appropriated with the climates. In order to stabilize the cooling capacity and also to maximize the use of solar energy, the system applies some controllers. Constant flow rate and on/off controller are applied for the hot water, chilled water and cooling water pumps. The hot water circulated by pump when the solar radiation is over than 400W/m², and the chilled water is continually circulated by pump and its temperature is kept constant 7 °C by absorption chiller. The cooling water is also continually circulated until the outlet temperature of cooling tower below than 27 ^oC. Furthermore, the three-way valve is used to control the hot water for generate vapor on absorption chiller. The system performance using that control system is shown in this study results.

Keywords: absorption chiller, control system, solar cooling, solar energy

Procedia PDF Downloads 269

Authors: Vanja Skoric

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The paper examines whether the impacts of artificial intelligence (AI) can be meaningfully addressed through the rights-based approach to AI design, investigating in particular how the inclusive, participatory process of assessing the AI impact would make this viable. There is a significant gap between envisioning rights-based AI systems and their practical application. Plausibly, internalizing human rights approach within AI design process might be achieved through identifying and assessing implications of AI features human rights, especially considering the case of vulnerable individuals and communities. However, there is no clarity or consensus on how such an instrument should be operationalised to usefully identify the impact, mitigate harms and meaningfully ensure relevant stakeholders’ participation. In practice, ensuring the meaningful inclusion of those individuals, groups, or entire communities who are affected by the use of the AI system is a prerequisite for a process seeking to assess human rights impacts and risks. Engagement in the entire process of the impact assessment should enable those affected and interested to access information and better understand the technology, product, or service and resulting impacts, but also to learn about their rights and the respective obligations and responsibilities of developers and deployers to protect and/or respect these rights. This paper will provide an overview of the study and practice of the participatory design process for AI, including inclusive impact assessment, its main elements, propose a framework, and discuss the lessons learned from the existing theory. In addition, it will explore pathways for enhancing and promoting individual and group rights through such engagement by discussing when, how, and whom to include, at which stage of the process, and what are the pre-requisites for meaningful and engaging. The overall aim is to ensure using the technology that works for the benefit of society, individuals, and particular (historically marginalised) groups.

Keywords: rights-based design, AI impact assessment, inclusion, harm mitigation

Procedia PDF Downloads 142

Authors: C. S. Subhashini, H. L. Premaratne

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Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

Procedia PDF Downloads 379